Aerodynamics Data Analyst

Grove, United Kingdom

Williams Racing

Williams Racing is one of the world’s leading Formula 1 teams. It exists purely to race in the top echelon of motor racing.

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Company Description

For almost 50 years, Williams Racing has been at the forefront of one of the fastest sports on the planet, being one of the top three most successful teams in history competing in the FIA Formula 1 World Championship. With an almost unrivalled heritage of engineering and racing F1 cars and unforgettable eras that demonstrate it is a force to be reckoned with, the British squad boasts 16 F1 World Championship titles to its name. 

Since its foundation in 1977 by the eminent, late Sir Frank Williams and engineering pioneer Sir Patrick Head, the team has won nine Constructors’ Championships, in association with Cosworth, Honda and Renault. Its roll call of drivers is legendary, with its seven Drivers’ Championship trophies being lifted by true icons of the sport: Alan Jones, Keke Rosberg, Nelson Piquet, Nigel Mansell, Alain Prost, Damon Hill and Jacques Villeneuve. The team has made history before and is out to make it again with a long-term mission to evolve and return to the front of the grid.

Job Description

The main objective of this role is to improve how faithfully our Wind Tunnel simulation and part selection methodology translate to the track. The role will involve liaising with various groups including Trackside Aero, Vehicle Performance, Vehicle Dynamics, CFD, Wind Tunnel as well as the Aero Development group. The role will involve co-ordination and analysis of Track, Wind Tunnel, CFD as well as DIL data to drive forward the correlation and performance methodologies in the Aero department.

This is a fantastic opportunity for an Aero Performance Engineer, Aerodynamicist, Vehicle Dynamicist, or Data Analyst/Scientist eager to expand their expertise into the aerodynamics space. The role will also involve collaborating with AI/ML engineers and applying AI/ML techniques to drive innovation and performance.

Operational Duties & Key Objectives:

  • Analysis of the correlation between Wind Tunnel and track and making recommendations to improve the Wind Tunnel environment to reduce any differences.
  • Involved in defining and analysing DIL experiments to understand how aero performance sensitivities affect lap time and how this should affect our part selection in the Wind Tunnel.
  • Involved in defining and analysing driver in the loop experiments to align aero performance and long-term setup directions.
  • Analysis of the correlation deficiencies between CFD and track and then working with the CFD group to improve our simulations.
  • Involved in R&D projects to deliver new instrumentation capability for the department.
  • Contributing to the improvement and development of our data analysis toolset for aero performance data, collaborating with dedicated software engineers.
  • Contributing to the improvement of whole car simulation correlation through cross department collaboration.

Requirements:

  • Strong communication and collaboration skills. Ability to work with a wide range of groups and integrate seamlessly.
  • A solid understanding of dynamic systems and a passion for system optimization
    • Understanding of race car vehicle dynamics and a track record of improving on track performance is a plus.
  • Experience of analysing performance and correlation data.
    • Familiarity with aerodynamics and aerodynamic data is highly beneficial
  • Familiar with scientific coding languages and able to develop your own data analysis tools.
  • Ability to present complex analysis in a concise manner that brings the data to life.
  • Degree in Aerodynamics, Aeronautical, Mechanical Engineering or Data Science (or equivalent).

Additional Information

#LI-AL2. #LI-AB1

Williams is an equal opportunity employer that values diversity and inclusion. We are happy to discuss reasonable job adjustments.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Analyst Jobs

Tags: Data analysis Engineering Machine Learning R R&D

Region: Europe
Country: United Kingdom

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